Single instruction multiple data (SIMD) architectures have become increasingly important as demand for video processing in electronic devices has increased. The SIMD architecture exploits the data parallelism that is abundant in data manipulations often found in media related applications, such as discrete cosine transforms (DCT) and filters. Data parallelism exists when a large mass of data of uniform type needs the same instruction performed on it. Thus, in contrast to a single instruction single data (SISD) architecture, in a SIMD architecture a single instruction may be used to effect an operation on a wide block of data. SIMD architecture exploits parallelism in the data stream while SISD can only operate on data sequentially.
An example of an application that takes advantage of SIMD is one where the same value is being added to a large number of data points, a common operation in many media application. One example of this is changing the brightness of a graphic image. Each pixel of the image may consist of three values for the brightness of the red, green ad blue portions of the color. To change the brightness, the R, G and B values, or alternatively the YUV values are read from memory, a value is added to it, and the resulting value is written back to memory. A SIMD processor enhances performance of this type of operation over that of a SISD processor. A reason for this improvement is that in SIMD architectures, data is understood to be in blocks and a number of values can be loaded at once. Instead of a series of instructions to incrementally fetch individual pixels, a SIMD processor will have a single instruction that effectively says “get all these pixels” Another advantage of SIMD machines is multiple pieces of data are operated on simultaneously. Thus, a single instruction can say “perform this operations on all the pixels.” Thus, SIMD machines are much more efficient in exploiting data parallelism than SISD machines.
A disadvantage of SIMD system is that they can require additional memory registers to support data which increases processor complexity and cost or they share resources such as registers with processing units of the CPU. This can cause competition for resources, conflicts, pipeline stalls and other events that adversely effect overall processor performance. A major disadvantage of SIMD architecture is the rigid requirement on data arrangement. The overhead to rearrange data in order to exploit data parallelism can significantly impact the speedup in computation and can even negate the performance gain achievable by a SIMD machine in comparison to a conventional SISD machine. Also, attaching a SIMD machine as an extension to a conventional SISD machine can cause various issues like synchronization, decoupling, etc.